Abstract
As an integral part of their occupational health care system, companies may be interested in the future disease-specific mortality patterns in their workforce. The mortality pattern is characterised by deaths from different competing disease groupings e.g. cancer of the respiratory system, cardiovascular disease, etc. In addition to monitoring the health of the workforce, mortality pattern predictions are central to the estimation of future pension, insurance or compensation liability.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Andersen, P. K., Borgan, Oernulf, Gill, R. D. & Keiding, N. (1993). Statistical models based on counting processes. Springer Series in Statistics. New York: Springer Verlag.
Jewell, N. P. & Kalbfleisch, J.D. (1992). Marker models in survival analysis and applications to issues associated with AIDS. In: AIDS Epidemiology: Methodological Issues. (ed. N.P. Jewell, K. Dietz & V. Farewell), 231–255. Boston: Birkhäuser.
Jewell, N. P. & Nielsen, J.P. (1993). A framework for consistent prediction rule based on markers. Biometrika, 80, 153–164.
Lindsey, J.K. (1995). Fitting Parametric Counting Processes by using Loglinear Models. Applied Statistics, 44, 201–212.
Rubin, D.B. (1976): Inference and missing data. Biometrika, 63, 581–92.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1998 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Eben, K., Vondráček, J., Binks, K. (1998). Mortality Pattern Prediction in Worker Cohorts. In: Payne, R., Green, P. (eds) COMPSTAT. Physica, Heidelberg. https://doi.org/10.1007/978-3-662-01131-7_3
Download citation
DOI: https://doi.org/10.1007/978-3-662-01131-7_3
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1131-5
Online ISBN: 978-3-662-01131-7
eBook Packages: Springer Book Archive